The Growing Impact of AI in the Software Development Process

by Capstone IT Solutions on June 26, 2024 in Artificial Intelligence

Artificial intelligence is poised to redefine the boundaries of what technology can achieve. Across industries, AI algorithms are empowering organizations to work smarter, faster, and more productively than ever—and the field of IT is no exception. According to a GitHub survey, 92% of developers now leverage AI coding tools to increase the efficiency and quality of their work.

While skilled IT professionals remain critical to the software development process, their roles are changing as artificial intelligence evolves. Tools like SpringAI, OpenAI Codex, Claude, and GitHub Copilot have enabled more intuitive coding processes, equipping developers with more time to innovate and produce highly adaptive applications for the future.

In this article, we’ll explore the role of AI in software development today and how we expect technology to impact the field in the long run.

How AI Is Transforming Software Development

The evolution of AI has rapidly accelerated in recent years, enabling integrations with coding platforms and all sorts of mainstream technologies. Organizations that once took a cautious approach—perhaps utilizing AI as a mechanism to accelerate software development or the quality assurance process—are now recognizing the value impact of a more widespread implementation.

As AI time investment ramps up and the overall experience improves, here are four ways artificial intelligence is introducing a new era of digital transformation.

1. Streamlining Coding Processes

Increased coding productivity is a continued goal of any organization and will be a fundamental component of AI in software development. As AI adoption continues to increase, today’s developers are no longer only using AI to streamline simple and repetitive tasks. Generative AI has advanced software development capabilities, and more importantly, the quality algorithmic prompts are on the rise.

Now, development teams are commonly using AI to:

  • Empower less experienced developers to produce initial code drafts that senior developers can later refine
  • Generate blocks of code to quickly insert into their existing codebase
  • Receive real-time improvement suggestions
  • Quickly refresh existing sections of code, thereby expediting the modernization effort

As a result, McKinsey estimates AI can now reduce the time required to write code by 35-45%.

Increasingly, software development teams are influencing or directing the coding process, rather than developing the code itself. The result is a shift of developers into more strategic roles—focused on aligning code with organizational standards and business goals rather than writing or rewriting alone.

2. Improving QA Processes

Manual quality assurance processes are often time-intensive to create or prone to scope limitations. AI, on the other hand, can quickly assemble simple test scenarios or run code checks looking for implementation exposures.

In the code review process, AI tools can identify a wide range of issues, from syntax errors to security vulnerabilities. As software projects enter the testing stage, AI automation can improve the testing process through automated debugging, proposed error resolution, or triggering AIOps algorithms to quickly implement updates into production for canary as well as A/B testing.

It is important to note that AI is not a replacement for qualified QA engineers, especially where environmental complexities exist. Ultimately, algorithms of any type will only be as effective as the people who build them, but AI tools can certainly increase the productivity output of your QA Team.

3. Accelerating Continuous Delivery

Continuous delivery is a fundamental tenet of any efficient software development methodology, and AI is taking the DevOps process to the next productivity level by rapidly improving delivery velocity. Here at Capstone IT Solutions, we are focused on integrating the world of DevOps and artificial intelligence operations (AIOps). It is the merging of these two key business pillars together that allows the acceleration of the entire software development lifecycle.

Leveraging AI to streamline the software development and QA processes to get more functionality to market, while essential, is only half the continuous delivery process. AIOps, the process of utilizing operational data—such as events, performance data, or security notifications—to feed AI algorithms accelerates problem resolution. Integrated DevOps pipelines and AIOps offers an elegant path to high-quality software delivered at greater pace.

4. Optimizing IT Strategies

Over the years, our industry has seen a project management evolution, in which the goal, “deliver on time, on budget,” has always been the ultimate measure of success. As our Solutions business engages in complex, large-budget projects, we see a continued desire to plan for everything upfront while running agile projects. This dichotomy is sometimes referred to as Waterfall vs. Agile.

Key stakeholders often want to understand complex project scope, risks, budget, and timelines and, in doing so, determine the risk profile of the overall effort. Development teams, in contrast, understand planning entire projects from the beginning cannot account for the “unknown unknowns” that emerge as projects unfold.

As we move forward, we see an intersection: AI will help mitigate day-to-day project management risks and budgetary exposures while allowing us to more effectively think “what if” about technology or finance options. When implemented well, IT strategy discussions spend less time in extensive and complex planning phases. Instead, they transition into a “decision to implementation” fast-fail model where risks are lower and impactful outcomes higher.

The Future of AI in Software Development

Looking ahead, AI is certain to exert an even greater influence on the software development field. Models are becoming more sophisticated and will continuously enable more personalized and adaptive software, capable of learning and evolving based on user interactions. This will enhance user experiences and drive innovation in ways previously unimaginable.

Streamlined code development, improved QA processes, and accelerated continuous delivery enable greater organizational productivity, bringing better software solutions to the market faster. Let’s face it, isn’t this the goal of all companies today? Let Capstone IT Solutions help you embrace AI’s potential.

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